AI Data Scientist

JR United Kingdom; London; Hybrid; GBP 50,000 - 80,000; Full time

Job summary

A leading global authority in higher education is seeking an AI Data Scientist to drive enhancements in LLM-based semantic analysis and collaborate on cloud-based data pipelines. This role offers the chance to impact global academic trends and work with diverse data sets in a data-heavy environment.

Qualifications

• Proven experience in AI, specifically with LLM.
• Skilled in integrating LLMs into cloud-based pipelines.
• Attention to detail in prompt engineering.

Responsibilities

• Enhance and deploy LLM-based semantic analysis.
• Collaborate to improve LLM workflows in cloud data pipelines.
• Develop novel LLM applications to support strategic goals.

Skills

AI

Large Language Model (LLM)

Python

SQL

Statistical Modelling

NLP

Data Science Techniques

Tools

AWS

DataBricks

Job description

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We are currently recruiting for a leading global authority in higher education for the role of AI Data Scientist. This is an exciting opportunity to impact global higher education, gain exposure to diverse international academic trends, and work in a data-heavy environment!

Role: AI Data Scientist

Location: Central London, 1 day per week in the office

What you'll be doing:

• Drive the enhancement and deployment of LLM-based semantic analysis within THE’s Impact Ranking and other academic evaluation projects.
• Collaborate with engineering teams to improve, rebuild, and integrate LLM workflows within scalable, cloud-based data pipelines.
• Apply advanced prompt-engineering techniques to improve LLM reliability and contribute to the company’s AI strategy.
• Identify and develop novel LLM applications across departments to support internal processes and strategic goals.

Main Skills/Requirements:

• Proven experience in AI, specifically Large Language Model (LLM).
• Proven experience with AWS, Python, SQL, and statistical modelling; skilled in integrating LLMs into cloud-based pipelines.
• Ability to apply NLP and data science techniques to real-world academic and sustainability data sets.
• Demonstrates rigorous attention to detail, especially in prompt engineering and evaluation of semantic outputs.
• Experience with Machine Learning or Predictive Modelling would be desirable.
• Familiarity with DataBricks, higher education/research data, sustainability metrics, and qualitative-to-quantitative analysis would be desirable.